[SPARK-1620] Handle uncaught exceptions in function run by Akka scheduler

If the intended behavior was that uncaught exceptions thrown in functions being run by the Akka scheduler would end up being handled by the default uncaught exception handler set in Executor, and if that behavior is, in fact, correct, then this is a way to accomplish that.  I'm not certain, though, that we shouldn't be doing something different to handle uncaught exceptions from some of these scheduled functions.

In any event, this PR covers all of the cases I comment on in [SPARK-1620](https://issues.apache.org/jira/browse/SPARK-1620).

Author: Mark Hamstra <markhamstra@gmail.com>

Closes #622 from markhamstra/SPARK-1620 and squashes the following commits:

071d193 [Mark Hamstra] refactored post-SPARK-1772
1a6a35e [Mark Hamstra] another style fix
d30eb94 [Mark Hamstra] scalastyle
3573ecd [Mark Hamstra] Use wrapped try/catch in Utils.tryOrExit
8fc0439 [Mark Hamstra] Make functions run by the Akka scheduler use Executor's UncaughtExceptionHandler
This commit is contained in:
Mark Hamstra 2014-05-14 10:07:25 -07:00 committed by Patrick Wendell
parent d58cb33ffa
commit 17f3075bc4
5 changed files with 36 additions and 18 deletions

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@ -30,7 +30,7 @@ import org.apache.spark.{Logging, SparkConf, SparkException}
import org.apache.spark.deploy.{ApplicationDescription, ExecutorState}
import org.apache.spark.deploy.DeployMessages._
import org.apache.spark.deploy.master.Master
import org.apache.spark.util.AkkaUtils
import org.apache.spark.util.{Utils, AkkaUtils}
/**
* Interface allowing applications to speak with a Spark deploy cluster. Takes a master URL,
@ -88,6 +88,7 @@ private[spark] class AppClient(
var retries = 0
registrationRetryTimer = Some {
context.system.scheduler.schedule(REGISTRATION_TIMEOUT, REGISTRATION_TIMEOUT) {
Utils.tryOrExit {
retries += 1
if (registered) {
registrationRetryTimer.foreach(_.cancel())
@ -99,6 +100,7 @@ private[spark] class AppClient(
}
}
}
}
def changeMaster(url: String) {
activeMasterUrl = url

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@ -166,6 +166,7 @@ private[spark] class Worker(
var retries = 0
registrationRetryTimer = Some {
context.system.scheduler.schedule(REGISTRATION_TIMEOUT, REGISTRATION_TIMEOUT) {
Utils.tryOrExit {
retries += 1
if (registered) {
registrationRetryTimer.foreach(_.cancel())
@ -178,6 +179,7 @@ private[spark] class Worker(
}
}
}
}
override def receive = {
case RegisteredWorker(masterUrl, masterWebUiUrl) =>

View file

@ -31,6 +31,7 @@ import scala.util.Random
import org.apache.spark._
import org.apache.spark.TaskState.TaskState
import org.apache.spark.scheduler.SchedulingMode.SchedulingMode
import org.apache.spark.util.Utils
/**
* Schedules tasks for multiple types of clusters by acting through a SchedulerBackend.
@ -139,7 +140,7 @@ private[spark] class TaskSchedulerImpl(
import sc.env.actorSystem.dispatcher
sc.env.actorSystem.scheduler.schedule(SPECULATION_INTERVAL milliseconds,
SPECULATION_INTERVAL milliseconds) {
checkSpeculatableTasks()
Utils.tryOrExit { checkSpeculatableTasks() }
}
}
}

View file

@ -155,7 +155,7 @@ private[spark] class BlockManager(
BlockManagerWorker.startBlockManagerWorker(this)
if (!BlockManager.getDisableHeartBeatsForTesting(conf)) {
heartBeatTask = actorSystem.scheduler.schedule(0.seconds, heartBeatFrequency.milliseconds) {
heartBeat()
Utils.tryOrExit { heartBeat() }
}
}
}

View file

@ -40,6 +40,7 @@ import tachyon.client.{TachyonFile,TachyonFS}
import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkException}
import org.apache.spark.deploy.SparkHadoopUtil
import org.apache.spark.executor.ExecutorUncaughtExceptionHandler
import org.apache.spark.serializer.{DeserializationStream, SerializationStream, SerializerInstance}
/**
@ -780,6 +781,18 @@ private[spark] object Utils extends Logging {
output.toString
}
/**
* Execute a block of code that evaluates to Unit, forwarding any uncaught exceptions to the
* default UncaughtExceptionHandler
*/
def tryOrExit(block: => Unit) {
try {
block
} catch {
case t: Throwable => ExecutorUncaughtExceptionHandler.uncaughtException(t)
}
}
/**
* A regular expression to match classes of the "core" Spark API that we want to skip when
* finding the call site of a method.